CN108267170B - Environment monitoring method and device - Google Patents
Environment monitoring method and device Download PDFInfo
- Publication number
- CN108267170B CN108267170B CN201711465771.8A CN201711465771A CN108267170B CN 108267170 B CN108267170 B CN 108267170B CN 201711465771 A CN201711465771 A CN 201711465771A CN 108267170 B CN108267170 B CN 108267170B
- Authority
- CN
- China
- Prior art keywords
- environment
- monitoring
- analysis
- index data
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Alarm Systems (AREA)
Abstract
The invention discloses an environment monitoring method and device, which are applied to wearable equipment and comprise the following steps: acquiring and storing environment monitoring index data obtained by monitoring the current environment by an environment sensor on wearable equipment; analyzing and predicting the environmental monitoring index data to obtain an analysis prediction result; and executing corresponding prompt or alarm operation on the wearable equipment according to the analysis prediction result. The environment monitoring device includes: the device comprises a data acquisition unit, an analysis prediction unit and a prompt alarm unit. The embodiment of the invention utilizes the characteristics of personal wear and portability of the wearable equipment to monitor the current ambient environment indexes of people at any time and any place in real time, and reminds users or alarms in time at the early stage of abnormal conditions, thereby ensuring the healthy life and personal safety of people.
Description
Technical Field
The invention relates to the technical field of wearable equipment, in particular to an environment monitoring method and device.
Background
In modern society, with the improvement of living standard and safety consciousness, healthy living environment and personal safety become more and more important to people. At present, environment monitoring equipment is generally fixed, and the requirement of a user for conveniently acquiring environment monitoring information cannot be met. In addition, the general environment monitoring equipment only provides environment monitoring index data at a certain time point, and the provided information amount is limited, the value is not high, and the user experience is poor.
Disclosure of Invention
The invention provides an environment monitoring method and device, and solves the technical problems of poor user experience caused by fixed position and limited information supply of the conventional environment monitoring equipment.
In order to achieve the technical purpose, the technical scheme of the invention is realized as follows:
according to one aspect of the invention, an environment monitoring method is provided, which is applied to wearable equipment and comprises the following steps:
acquiring and storing environment monitoring index data obtained by monitoring the current environment by an environment sensor on the wearable device;
analyzing and predicting the environmental monitoring index data to obtain an analysis and prediction result;
and executing corresponding prompt or alarm operation on the wearable equipment according to the analysis prediction result.
According to another aspect of the present invention, there is provided an environment monitoring apparatus applied to a wearable device, including:
the data acquisition unit is used for acquiring and storing environment monitoring index data obtained by monitoring the current environment by the environment sensor on the wearable device;
the analysis and prediction unit is used for carrying out analysis and prediction processing on the environment monitoring index data to obtain an analysis and prediction result;
and the prompt alarm unit is used for executing corresponding prompt or alarm operation on the wearable equipment according to the analysis prediction result.
According to still another aspect of the present invention, there is provided an electronic apparatus including: the environment monitoring system comprises a memory and a processor, wherein the memory and the processor are in communication connection through an internal bus, the memory stores program instructions capable of being executed by the processor, and the program instructions are capable of realizing the environment monitoring method in one aspect of the invention when being executed by the processor.
The invention has the beneficial effects that: the environment monitoring method and the environment monitoring device are applied to wearable equipment, environment monitoring index data obtained by monitoring the current environment through an environment sensor on the wearable equipment are obtained and stored, the environment monitoring index data are analyzed, predicted and processed to obtain an analysis prediction result, and corresponding prompt or alarm operation is executed on the wearable equipment according to the analysis prediction result. Therefore, the characteristics of personal wearing and portability of the wearable device are utilized, the current ambient environment indexes of people can be monitored in real time at any time and any place, and a user can conveniently acquire environment monitoring information. In addition, the environment index data is further analyzed on the basis of monitoring, the possible danger is predicted according to the change trend of various environment indexes, and the user is timely reminded or the alarm is given, so that people can find and timely handle the danger in the early stage, and the health and personal safety of people are guaranteed.
Drawings
FIG. 1 is a flow chart of an environmental monitoring method in accordance with an embodiment of the present invention;
FIG. 2 is a flowchart illustrating an environmental monitoring method according to an embodiment of the present invention;
FIG. 3 is a flow diagram of environmental analysis forecasting, according to one embodiment of the present invention;
FIG. 4 is a block diagram of an environmental monitoring device in accordance with one embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The design concept of the invention is as follows: the environment monitoring system aims at the problems that in the prior art, generally fixed equipment is adopted for environment monitoring, deep analysis is lacked for environment indexes, and the use experience is poor. The embodiment of the invention provides an environment monitoring method and device, which are applied to wearable equipment such as a smart watch. Wearable devices are rapidly developed at present, have own computing capability and resources, and are generally embedded into various MEMS (Micro-Electro-Mechanical systems) sensors, so as to provide software and hardware support for data acquisition, operation and signal processing. In addition, wearable equipment generally can wear on one's body for a long time, so, through on the wearable equipment of environment monitoring function integration, can monitor surrounding environmental conditions and unusual anytime and anywhere, strengthened user experience to people's healthy life and personal safety have been ensured.
Fig. 1 is a flowchart of an environment monitoring method according to an embodiment of the present invention, and referring to fig. 1, the environment monitoring method according to the embodiment is applied to a wearable device, and includes the following steps:
step S101, obtaining and storing environment monitoring index data obtained by monitoring the current environment by an environment monitoring sensor on the wearable device;
step S102, analyzing and predicting the environmental monitoring index data to obtain an analysis and prediction result;
and S103, executing corresponding prompt or alarm operation on the wearable equipment according to the analysis prediction result.
As shown in fig. 1, the environment monitoring method of the embodiment can acquire the environment monitoring data acquired by the environment monitoring sensor above the wearable device at any time, then perform analysis, prediction and processing to obtain a result, and execute a prompt or alarm operation according to different results, so that a user can conveniently acquire information of the current environment in time. Moreover, the displayed information is richer and more valuable by analyzing, predicting and processing the environmental monitoring data, so that the user experience and the market competitiveness of the wearable equipment are improved, and the application field is expanded.
In specific application, the method can integrate CO and CO in wearable equipment (such as a smart watch)2And the environment sensors such as temperature, humidity and the like, and the ambient environment data is collected through the environment sensors and then detected and analyzed. Meanwhile, information such as the environment index and the analysis result is displayed on an environment monitoring interface of the intelligent watch in real time, and reasonable suggestions are made for the user according to the current environment index and are also displayed for the user. Therefore, when the abnormal condition of the environment is found, the alarm is timely reminded or given, and the loss is avoided or reduced.
The environmental monitoring method according to an embodiment is specifically described below with reference to fig. 2 and 3.
Referring to fig. 2, the process begins,
step S201 is executed first, and an environment sensor collects data;
it should be noted that various environmental sensors, such as an atmosphere monitoring sensor, a humidity sensor, a temperature sensor, etc., may be integrated on the wearable device of the present embodiment.
Step S202, analyzing and predicting environmental monitoring index data;
after the environment monitoring data are obtained, the environment monitoring data are further analyzed and predicted in the step, so that the problems that only monotonous and messy data are displayed, readability is poor, and information value is low are solved, and the requirement for acquiring various environment information of users is met.
Step S203, displaying data;
in this step, the collected environment monitoring data is directly displayed or the abnormal environment information is directly displayed in this embodiment, it should be noted that what is displayed in this step may be a real-time value of the current environment, that is, the index data corresponding to the collection time point is displayed, and the user can conveniently know the environment condition at the current time point by displaying the index data. This is different from the foregoing step S202 in that, in the step S202, the obtained environmental monitoring index data is deeply analyzed, and the data in a period of time and the trend of the environmental monitoring data are combined for prediction, so that the provided information is more valuable, and the hidden danger can be found and predicted.
And step S204, judging whether the environment is abnormal, if so, executing step S205, otherwise, returning to execute step S201.
This step is to determine whether the current environment is abnormal or not, that is, whether the index value of the current environment deviates from the normal range or not, if so, it may be determined to be abnormal, otherwise, it is determined to be normal, based on the analysis of the environment monitoring index data in step S202.
And step S205, local alarm or remote alarm.
In this step, according to the judgment result of the environmental abnormality in step S204, alarms of different levels, such as local alarms or alarm operations, are executed. In one embodiment, the alarm is set to a level, different alarms are issued according to the severity of the anomaly, and if the severity is slight, a local alarm is issued. Here, the local means information on the wearable device, for example, an alarm sound is emitted on the wearable device while accompanying a vibration, and the reason of the abnormality and a risk avoidance measure that can be taken are displayed on the wearable device. Remote alarm, be in advance with wearable equipment and a plurality of remote alarm center server set up the connection, when the environment is unusual, send alarm notice to corresponding alarm center according to unusual kind, for example, send fire alarm notice to fire alarm center server, so can report to the police the very first time, protect people's life and property safety.
The focus of an embodiment of the present invention is to analyze and predict the collected environmental monitoring index data, i.e., step S202 in fig. 2, where step S202 is described in conjunction with fig. 3.
The process starts, and step S301 is executed to obtain data;
acquiring data here refers to acquiring basic data of the current environment from environment sensors on the wearable device, for example, carbon monoxide CO and carbon dioxide CO at 11 am2Concentration value, humidity value, temperature value, etc.
Step S302, storing the data in a cache;
in the step, on the basis of acquiring data acquired by each environmental sensor on the wearable device in the last step, storing the basic data in a cache with a preset length in a first-in first-out mode; the preset length is 128KB, for example, and the first-in first-out mode is adopted to ensure timeliness of data, and the reliability and accuracy of the analysis prediction result are ensured by using the newer data to perform analysis prediction.
Of course, in other embodiments of the present invention, the storage may not be performed in a first-in first-out manner, which is not limited to this.
Step S303, comparing with an index range;
it should be noted that, in the present embodiment, each environmental index monitored by the monitoring system, taking an index of carbon monoxide in the atmosphere as an example, corresponds to an index range, and the index range represents an index value in which the environment is normal.
The index range is, for example, [ 10, 30 ] (in mg/m)3Milligrams per cubic meter), after the carbon monoxide data is collected once, the collected carbon monoxide data is compared with the index range in step S303 for subsequent processing.
Step S304, judging whether the index range exceeds a preset threshold value; if so, step S305 is performed, otherwise, step S301 is performed,
in the step, whether the acquired basic data exceeds the index range and reaches a preset threshold value is judged, wherein the fact that the acquired basic data exceeds the index range and reaches the preset threshold value means that the absolute value of the difference value between the basic data and the index range is larger than or equal to the preset threshold value. For example, if the data of carbon monoxide in one acquisition is 50 and the index range of carbon monoxide is [ 10, 30 ], the difference 20 between 50 and the upper limit value 30 of the index range exceeds the preset threshold 15, and it can be determined that the data of carbon monoxide exceeding the index range reaches the preset threshold.
In step S305, a risk situation is predicted.
When the current environment is determined to be abnormal, in the step, relevant environmental monitoring index data (for example, environmental monitoring index data relevant to fire and environmental monitoring index data relevant to gas poisoning) are input into a pre-trained dangerous condition model, the relative change trend of each environmental index is analyzed, the dangerous condition possibly occurring in the current environment is predicted, and an analysis prediction result is obtained.
It should be noted that, when the data exceeds the index range and reaches the preset threshold, it indicates that there is an abnormality and a danger in the current environment, which requires judgment and prediction of a dangerous condition, and timely reminds the user to discover early processing. Before dangerous conditions such as fire, gas leakage and the like occur, CO and CO in the air2The concentration, the temperature, the humidity and other environmental indexes have a certain change rule, therefore, in the embodiment, machine learning methods such as a Support Vector Machine (SVM), a neural network and the like are adopted to perform offline training in advance to train CO and CO under different dangerous conditions2And the corresponding change models of the air indexes such as temperature and humidity, namely, the corresponding dangerous condition models.
Then, in this step, the relative change trend of each environmental index is analyzed according to the trained danger condition model and machine learning and other methods for the environmental monitoring index data stored in the cache for the latest period of time (for example, one month), the type and grade of the danger (such as fire, gas leakage and the like) which may occur at present are predicted, and a prompt is timely sent out in the early stage of the occurrence of the danger condition, so that people can early discover and early handle the abnormal condition, and the health condition and personal safety of people are guaranteed.
Considering that wearable devices are typically limited in computing power and resources, it is desirable to minimize the power consumption of the system. In this embodiment, a corresponding control instruction input by a user on an interactive interface of the wearable device is received, and the environment monitoring function is turned on or off through a system call interface. That is to say, the system is provided with a calling interface, and the control functions of opening and closing the environment monitoring and the like by the user are realized. The user can freely set the on and off of the environment monitoring system according to actual conditions, and the like, so that the power consumption is reduced.
An embodiment of the present invention further provides an environment monitoring apparatus, fig. 4 is a block diagram of an environment monitoring apparatus according to an embodiment of the present invention, and referring to fig. 4, the environment monitoring apparatus 400 is applied to a wearable device, and includes:
the data acquisition unit 401 is configured to acquire and store environment monitoring index data obtained by monitoring a current environment by an environment sensor on the wearable device;
an analysis and prediction unit 402, configured to perform analysis and prediction processing on the environmental monitoring index data to obtain an analysis and prediction result;
and a prompt alarm unit 403, configured to execute a corresponding prompt or alarm operation on the wearable device according to the analysis prediction result.
Here, the wearable device is, for example, an electronic device such as a smart watch, a smart bracelet, smart glasses, and the like.
In an embodiment of the present invention, the analysis and prediction unit 402 is configured to compare the environmental monitoring index data with a corresponding index range, and determine that an abnormality occurs in the current environment when the environmental monitoring index data exceeds the index range and reaches a preset threshold.
In an embodiment of the present invention, the analysis and prediction unit 402 is further configured to, after determining that the current environment is abnormal, input the relevant environmental monitoring index data into a pre-trained dangerous condition model, analyze a relative change trend of each environmental index, and predict a dangerous condition that may occur in the current environment, so as to obtain an analysis and prediction result.
In an embodiment of the present invention, the prompt alarm unit 403 is configured to perform different levels of alarm operations on the wearable device according to the analysis and prediction result of the dangerous situation that may occur in the current environment; and executing prompt operation on the wearable equipment according to the analysis prediction result that no abnormality occurs in the current environment.
In an embodiment of the present invention, the data acquiring unit 401 is configured to acquire an atmospheric monitoring sensor, a humidity sensor, and a temperature sensor on the wearable device; the wearable device is used for acquiring data acquired by each environmental sensor on the wearable device and storing the data in a cache with a preset length in a first-in first-out mode;
in one embodiment of the present invention, the environmental monitoring device 400 further comprises:
and the switch control unit is used for receiving a corresponding control instruction input by a user on the wearable equipment interactive interface and starting or closing the environment monitoring function through a system call interface.
It should be noted that the working process of the environment monitoring apparatus in this embodiment corresponds to the implementation steps of the environment monitoring method, and therefore, for parts that are not described in detail in this embodiment, reference may be made to the description in the foregoing embodiment, which is not described herein again.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. As shown in fig. 5, the electronic device includes a memory 501 and a processor 502, the memory 501 and the processor 502 are communicatively connected through an internal bus 503, the memory 501 stores program instructions that can be executed by the processor 502, and the program instructions, when executed by the processor 502, can implement the environment monitoring method described above.
In addition, the logic instructions in the memory 501 may be implemented in the form of software functional units and may be stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention or a part thereof, which essentially contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Another embodiment of the present invention provides a computer-readable storage medium storing computer instructions that cause the computer to perform the above-described method.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It is to be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
In the description of the present invention, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description. Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
While the foregoing is directed to embodiments of the present invention, other modifications and variations of the present invention may be devised by those skilled in the art in light of the above teachings. It should be understood by those skilled in the art that the foregoing detailed description is for the purpose of illustrating the invention rather than the foregoing detailed description, and that the scope of the invention is defined by the claims.
Claims (7)
1. An environment monitoring method is applied to wearable equipment and comprises the following steps:
acquiring and storing environment monitoring index data obtained by monitoring the current environment by an environment sensor on the wearable device;
analyzing and predicting the environmental monitoring index data to obtain an analysis and prediction result;
executing corresponding prompt or alarm operation on the wearable equipment or sending an alarm notification to a corresponding alarm center according to the analysis prediction result;
the analyzing and predicting processing of the environmental monitoring index data to obtain an analyzing and predicting result comprises the following steps:
after determining that the current environment is abnormal, inputting relevant environment monitoring index data into a pre-trained dangerous condition model, analyzing the relative change trend of each environment index, predicting the dangerous condition possibly occurring in the current environment, and obtaining an analysis prediction result;
the dangerous condition model is subjected to offline training in advance by adopting a Support Vector Machine (SVM) or neural network machine learning method;
wherein executing a corresponding prompt or alarm operation on the wearable device according to the analysis prediction result comprises:
according to the analysis and prediction results of the dangerous conditions possibly occurring in the current environment, alarm operations of different levels are executed on the wearable equipment;
and executing prompt operation on the wearable equipment according to the analysis prediction result that no abnormality occurs in the current environment.
2. The environmental monitoring method of claim 1, wherein analyzing and predicting the environmental monitoring indicator data comprises:
and comparing the environment monitoring index data with a corresponding index range, and determining that the current environment is abnormal when the environment monitoring index data exceeds the index range and reaches a preset threshold value.
3. The environment monitoring method according to claim 1, wherein obtaining environment monitoring index data obtained by monitoring a current environment by an environment sensor on the wearable device comprises:
acquiring an atmosphere monitoring sensor, a humidity sensor and a temperature sensor on the wearable device;
the environmental monitoring index data that environmental sensor monitored current environment on acquireing wearable equipment and obtain and save include:
after data acquired by each environmental sensor on the wearable equipment are acquired, the data are stored in a cache with a preset length in a first-in first-out mode;
the method further comprises the following steps:
and receiving a corresponding control instruction input by a user on an interactive interface of the wearable device, and starting or closing the environment monitoring function through a system call interface.
4. The utility model provides an environment monitoring device which characterized in that is applied to wearable equipment, includes:
the data acquisition unit is used for acquiring and storing environment monitoring index data obtained by monitoring the current environment by the environment sensor on the wearable device;
the analysis and prediction unit is used for carrying out analysis and prediction processing on the environment monitoring index data to obtain an analysis and prediction result;
the prompt alarm unit is used for executing corresponding prompt or alarm operation on the wearable equipment or sending an alarm notice to a corresponding alarm center according to the analysis and prediction result;
the analysis and prediction unit is further used for inputting the relevant environment monitoring index data into a pre-trained dangerous condition model after determining that the current environment is abnormal, analyzing the relative change trend of each environmental index, predicting the dangerous condition which possibly occurs in the current environment, and obtaining an analysis and prediction result;
the dangerous condition model is subjected to offline training in advance by adopting a Support Vector Machine (SVM) or neural network machine learning method;
the prompting and alarming unit is used for executing alarming operations of different levels on the wearable equipment according to the analysis and prediction result of the dangerous condition possibly occurring in the current environment; and executing prompt operation on the wearable equipment according to the analysis prediction result that no abnormality occurs in the current environment.
5. The environmental monitoring device of claim 4,
and the analysis and prediction unit is used for comparing the environment monitoring index data with a corresponding index range, and determining that the current environment is abnormal when the environment monitoring index data exceeds the index range and reaches a preset threshold value.
6. The environmental monitoring device of claim 4,
the data acquisition unit is used for acquiring an atmosphere monitoring sensor, a humidity sensor and a temperature sensor on the wearable device; the wearable device is used for acquiring data acquired by each environmental sensor on the wearable device and storing the data in a cache with a preset length in a first-in first-out mode;
the device also includes:
and the switch control unit is used for receiving a corresponding control instruction input by a user on the interactive interface of the wearable device and starting or closing the environment monitoring function through a system call interface.
7. An electronic device, characterized in that the electronic device comprises: a memory and a processor, the memory and the processor being communicatively connected via an internal bus, the memory storing program instructions executable by the processor, the program instructions when executed by the processor being capable of implementing the environmental monitoring method of any one of claims 1-3.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711465771.8A CN108267170B (en) | 2017-12-28 | 2017-12-28 | Environment monitoring method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711465771.8A CN108267170B (en) | 2017-12-28 | 2017-12-28 | Environment monitoring method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108267170A CN108267170A (en) | 2018-07-10 |
| CN108267170B true CN108267170B (en) | 2021-06-22 |
Family
ID=62772735
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711465771.8A Active CN108267170B (en) | 2017-12-28 | 2017-12-28 | Environment monitoring method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108267170B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109739165A (en) * | 2019-01-16 | 2019-05-10 | 秦皇岛海涛万福环保设备股份有限公司 | Outdoor ceremony park monitoring method and monitoring system |
| CN112050970B (en) * | 2020-08-14 | 2022-09-09 | 中国神华能源股份有限公司国华电力分公司 | Environment monitoring method and device |
| CN113219871B (en) * | 2021-05-07 | 2022-04-01 | 淮阴工学院 | Curing room environmental parameter detecting system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106383463A (en) * | 2016-09-06 | 2017-02-08 | 华中科技大学 | Construction environmental monitoring system and method based on safety helmet |
| CN106595757A (en) * | 2016-11-29 | 2017-04-26 | 西南石油大学 | Environment monitoring method and system |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101413961A (en) * | 2007-10-19 | 2009-04-22 | 北京中立格林控制技术有限公司 | Multifunctional air environment monitoring control device |
| CN204950975U (en) * | 2015-07-01 | 2016-01-13 | 京东方科技集团股份有限公司 | Wearable electronic device |
| CN107290482A (en) * | 2017-06-02 | 2017-10-24 | 广西明成科技发展有限公司 | A kind of industrial environment monitoring system |
-
2017
- 2017-12-28 CN CN201711465771.8A patent/CN108267170B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106383463A (en) * | 2016-09-06 | 2017-02-08 | 华中科技大学 | Construction environmental monitoring system and method based on safety helmet |
| CN106595757A (en) * | 2016-11-29 | 2017-04-26 | 西南石油大学 | Environment monitoring method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108267170A (en) | 2018-07-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109313104B (en) | Machine monitoring | |
| EP3407200B1 (en) | Method and device for updating online self-learning event detection model | |
| CN108267170B (en) | Environment monitoring method and device | |
| CN109001649A (en) | A kind of power supply smart diagnostic system and guard method | |
| CN108268893B (en) | Chemical industry park early warning method and device based on machine learning | |
| CN108597176A (en) | Wearable device based safety early warning method and wearable device | |
| CN110081318A (en) | A kind of pipe network monitor system | |
| CN110226934B (en) | Fall detection method and device and wrist strap type equipment | |
| CN112949546A (en) | Off-duty detection method and device based on artificial intelligence perception of station service state | |
| CN113192283A (en) | Wireless fire early warning system with multi-sensor information fusion | |
| CN116433029A (en) | Power operation risk assessment method, system, equipment and storage medium | |
| CN106913313B (en) | Sleep monitoring method and system | |
| CN109767599A (en) | A kind of intelligent alarm method and its system | |
| CN111750925A (en) | Equipment aging prediction system, method and device | |
| US20170183016A1 (en) | Early warning system for locomotive bearings failures | |
| CN107007292B (en) | Method for learning fatigue | |
| EP3472742A1 (en) | Machine monitoring | |
| CN112386249B (en) | Fall detection method and device, equipment and storage medium | |
| CN109118125B (en) | Urban environment and economy comprehensive evaluation system | |
| CN113884130A (en) | Cable aging prediction method, device and equipment based on cable well environment monitoring | |
| CN221484597U (en) | Water treatment operation monitoring system | |
| CN117558103B (en) | Emergency rescue method and device based on intelligent wearable equipment | |
| CN117133108A (en) | High-voltage test early warning method, device, equipment and storage medium based on safety clothing | |
| CN118376353B (en) | Gas safety monitoring method, device, equipment and storage medium | |
| CN115127514B (en) | Height measurement method, device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20191114 Address after: 266104 Laoshan Qingdao District North House Street investment service center room, Room 308, Shandong Applicant after: GEER TECHNOLOGY CO., LTD. Address before: 266061, No. 3, building 18, Qinling Mountains Road, Laoshan District, Shandong, Qingdao 401 Applicant before: Qingdao real time Technology Co., Ltd. |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |